Participants in the financial services industry utilize financial models or mathematical descriptions of the values of one or more financial variables under various market conditions. For example, credit models, such as various copula credit models, are used to describe the default probability of debt instruments based on market conditions such as spreads, whether other debt instruments have defaulted, etc. Many of these credit models take into account the relationships between the default probabilities of various debt instruments. Credit models may be used to value debt instruments themselves or credit derivative instruments based on underlying debt instruments. For example, credit models may be used to value the tranches of a collateralized debt obligation (CDO) or a credit swap. Other examples of financial models may include the Black-Scholes Model for describing the value of an option contract based on market conditions including the price of the underlying security, the strike price, etc.
Often existing financial models include implicit assumptions about the market and the relationships between the modeled financial variables. The consequences, and sometimes the existence, of these implicit assumptions in a financial model may not be immediately apparent to the modeler. It can be appreciated that if a financial model includes implicit assumptions that are absurd or do not match actual market conditions, the value of the model may be limited.
Also, existing financial models often require complex computations to find conditional distributions of financial variables, e.g. the distribution of a financial variable considering the known values of other financial variables. This can make it difficult to incorporate real-time data into a financial model. For example, correlation between the default probabilities of the underlying debt instruments of a collateralized debt obligation (CDO) may affect the values of the various tranches if some of the underlying debt instruments default. In fact, if the default probabilities of the underlying debt instruments show a high degree of correlation, then the value of higher tranches of the CDO may suffer even if there are just a few defaults.
What is needed are improved systems and methods for extracting the implications of financial models and a framework for using and improving the models. What is also needed are methods and systems for considering conditional probabilities of financial variables in financial models.